SOTAVerified

Super-Resolution

Super-Resolution is a task in computer vision that involves increasing the resolution of an image or video by generating missing high-frequency details from low-resolution input. The goal is to produce an output image with a higher resolution than the input image, while preserving the original content and structure.

( Credit: MemNet )

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1301–1350 of 3874 papers

TitleStatusHype
Edge Storage Management Recipe with Zero-Shot Data Compression for Road Anomaly Detection—0
DWA: Differential Wavelet Amplifier for Image Super-ResolutionCode0
Enhancing Building Semantic Segmentation Accuracy with Super Resolution and Deep Learning: Investigating the Impact of Spatial Resolution on Various Datasets—0
Cross-Spatial Pixel Integration and Cross-Stage Feature Fusion Based Transformer Network for Remote Sensing Image Super-Resolution—0
RefVSR++: Exploiting Reference Inputs for Reference-based Video Super-resolution—0
DeSRA: Detect and Delete the Artifacts of GAN-based Real-World Super-Resolution ModelsCode1
Compound Attention and Neighbor Matching Network for Multi-contrast MRI Super-resolution—0
Source Identification: A Self-Supervision Task for Dense Prediction—0
Dual Arbitrary Scale Super-Resolution for Multi-Contrast MRICode1
Spatio-Temporal Perception-Distortion Trade-off in Learned Video SRCode0
ACDMSR: Accelerated Conditional Diffusion Models for Single Image Super-Resolution—0
Solving Linear Inverse Problems Provably via Posterior Sampling with Latent Diffusion ModelsCode1
Enhancing Super-Resolution Networks through Realistic Thick-Slice CT SimulationCode0
Line Spectrum Estimation and Detection with Few-bit ADCs: Theoretical Analysis and Generalized NOMP Algorithm—0
WaveMixSR: A Resource-efficient Neural Network for Image Super-resolutionCode1
A Motion Assessment Method for Reference Stack Selection in Fetal Brain MRI Reconstruction Based on Tensor Rank ApproximationCode0
RBSR: Efficient and Flexible Recurrent Network for Burst Super-ResolutionCode1
Semantic Segmentation Using Super Resolution Technique as Pre-Processing—0
SPDER: Semiperiodic Damping-Enabled Object Representation—0
Cutting-Edge Techniques for Depth Map Super-Resolution—0
Novel Hybrid-Learning Algorithms for Improved Millimeter-Wave Imaging SystemsCode0
Store and Fetch Immediately: Everything Is All You Need for Space-Time Video Super-resolutionCode0
Iterative-in-Iterative Super-Resolution Biomedical Imaging Using One Real Image—0
SHISRCNet: Super-resolution And Classification Network For Low-resolution Breast Cancer Histopathology ImageCode1
SuperBench: A Super-Resolution Benchmark Dataset for Scientific Machine LearningCode1
Real-World Video for Zoom Enhancement based on Spatio-Temporal Coupling—0
Creating Realistic Anterior Segment Optical Coherence Tomography Images using Generative Adversarial Networks—0
Simultaneous Image-to-Zero and Zero-to-Noise: Diffusion Models with Analytical Image AttenuationCode1
Directional diffusion models for graph representation learning—0
Minimalist and High-Quality Panoramic Imaging with PSF-aware TransformersCode1
Super-Resolution of BVOC Emission Maps Via Domain AdaptationCode0
DiffuseIR:Diffusion Models For Isotropic Reconstruction of 3D Microscopic Images—0
Dynamic Implicit Image Function for Efficient Arbitrary-Scale Image RepresentationCode1
HSR-Diff:Hyperspectral Image Super-Resolution via Conditional Diffusion Models—0
Using super-resolution for enhancing visual perception and segmentation performance in veterinary cytology—0
Optical Coherence Tomography Image Enhancement via Block Hankelization and Low Rank Tensor Network Approximation—0
Evaluating Loss Functions and Learning Data Pre-Processing for Climate Downscaling Deep Learning Models—0
Super-resolving sparse observations in partial differential equations: A physics-constrained convolutional neural network approach—0
Super-Resolution Radar Imaging with Sparse Arrays Using a Deep Neural Network Trained with Enhanced Virtual DataCode1
FALL-E: A Foley Sound Synthesis Model and StrategiesCode1
CANDID: Correspondence AligNment for Deep-burst Image Denoising—0
Deep learning techniques for blind image super-resolution: A high-scale multi-domain perspective evaluationCode1
Generalizable One-shot Neural Head Avatar—0
Effects of Data Enrichment with Image Transformations on the Performance of Deep Networks—0
TransMRSR: Transformer-based Self-Distilled Generative Prior for Brain MRI Super-ResolutionCode1
Learning Image-Adaptive Codebooks for Class-Agnostic Image Restoration—0
SARN: Structurally-Aware Recurrent Network for Spatio-Temporal DisaggregationCode0
2DeteCT -- A large 2D expandable, trainable, experimental Computed Tomography dataset for machine learningCode1
HRTF upsampling with a generative adversarial network using a gnomonic equiangular projectionCode1
HQ-50K: A Large-scale, High-quality Dataset for Image RestorationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1super-resolutionAverage PSNR20.41—Unverified